// ---------------------------------------------------------------------
//
// Copyright (C) 2008 - 2023 by the deal.II authors
//
// This file is part of the deal.II library.
//
// The deal.II library is free software; you can use it, redistribute
// it, and/or modify it under the terms of the GNU Lesser General
// Public License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
// The full text of the license can be found in the file LICENSE.md at
// the top level directory of deal.II.
//
// ---------------------------------------------------------------------

#ifndef dealii_trilinos_parallel_block_vector_h
#define dealii_trilinos_parallel_block_vector_h


#include <deal.II/base/config.h>

#ifdef DEAL_II_WITH_TRILINOS

#  include <deal.II/lac/block_indices.h>
#  include <deal.II/lac/block_vector_base.h>
#  include <deal.II/lac/exceptions.h>
#  include <deal.II/lac/trilinos_vector.h>

#  include <functional>

DEAL_II_NAMESPACE_OPEN

// forward declaration
#  ifndef DOXYGEN
template <typename Number>
class BlockVectorBase;

namespace TrilinosWrappers
{
  // forward declaration
  namespace MPI
  {
    class BlockVector;
  }
  class BlockSparseMatrix;
} // namespace TrilinosWrappers
#  endif

/**
 * @addtogroup TrilinosWrappers
 * @{
 */

namespace TrilinosWrappers
{
  namespace MPI
  {
    /**
     * An implementation of block vectors based on the vector class
     * implemented in TrilinosWrappers. While the base class provides for most
     * of the interface, this class handles the actual allocation of vectors
     * and provides functions that are specific to the underlying vector type.
     *
     * The model of distribution of data is such that each of the blocks is
     * distributed across all MPI processes named in the MPI communicator.
     * I.e. we don't just distribute the whole vector, but each component. In
     * the constructors and reinit() functions, one therefore not only has to
     * specify the sizes of the individual blocks, but also the number of
     * elements of each of these blocks to be stored on the local process.
     *
     * @ingroup Vectors
     * @ingroup TrilinosWrappers @see
     * @ref GlossBlockLA "Block (linear algebra)"
     */
    class BlockVector : public dealii::BlockVectorBase<MPI::Vector>
    {
    public:
      /**
       * Typedef the base class for simpler access to its own alias.
       */
      using BaseClass = dealii::BlockVectorBase<MPI::Vector>;

      /**
       * Typedef the type of the underlying vector.
       */
      using BlockType = BaseClass::BlockType;

      /**
       * Import the alias from the base class.
       */
      using value_type      = BaseClass::value_type;
      using pointer         = BaseClass::pointer;
      using const_pointer   = BaseClass::const_pointer;
      using reference       = BaseClass::reference;
      using const_reference = BaseClass::const_reference;
      using size_type       = BaseClass::size_type;
      using iterator        = BaseClass::iterator;
      using const_iterator  = BaseClass::const_iterator;

      /**
       * Default constructor. Generate an empty vector without any blocks.
       */
      BlockVector() = default;

      /**
       * Constructor. Generate a block vector with as many blocks as there are
       * entries in @p partitioning.  Each IndexSet together with the MPI
       * communicator contains the layout of the distribution of data among
       * the MPI processes.
       */
      explicit BlockVector(const std::vector<IndexSet> &parallel_partitioning,
                           const MPI_Comm communicator = MPI_COMM_WORLD);

      /**
       * Creates a BlockVector with ghost elements. See the respective
       * reinit() method for more details. @p ghost_values may contain any
       * elements in @p parallel_partitioning, they will be ignored.
       */
      BlockVector(const std::vector<IndexSet> &parallel_partitioning,
                  const std::vector<IndexSet> &ghost_values,
                  const MPI_Comm               communicator,
                  const bool                   vector_writable = false);

      /**
       * Copy-Constructor. Set all the properties of the parallel vector to
       * those of the given argument and copy the elements.
       */
      BlockVector(const BlockVector &v);

      /**
       * Move constructor. Creates a new vector by stealing the internal data
       * of the vector @p v.
       */
      BlockVector(BlockVector &&v) noexcept;

      /**
       * Creates a block vector consisting of <tt>num_blocks</tt> components,
       * but there is no content in the individual components and the user has
       * to fill appropriate data using a reinit of the blocks.
       */
      explicit BlockVector(const size_type num_blocks);

      /**
       * Destructor. Clears memory
       */
      ~BlockVector() override = default;

      /**
       * Copy operator: fill all components of the vector that are locally
       * stored with the given scalar value.
       */
      BlockVector &
      operator=(const value_type s);

      /**
       * Copy operator for arguments of the same type.
       */
      BlockVector &
      operator=(const BlockVector &v);

      /**
       * Move the given vector. This operator replaces the present vector with
       * @p v by efficiently swapping the internal data structures.
       */
      BlockVector &
      operator=(BlockVector &&v) noexcept;

      /**
       * Another copy function. This one takes a deal.II block vector and
       * copies it into a TrilinosWrappers block vector. Note that the number
       * of blocks has to be the same in the vector as in the input vector.
       * Use the reinit() command for resizing the BlockVector or for changing
       * the internal structure of the block components.
       *
       * Since Trilinos only works on doubles, this function is limited to
       * accept only one possible number type in the deal.II vector.
       */
      template <typename Number>
      BlockVector &
      operator=(const ::dealii::BlockVector<Number> &v);

      /**
       * Reinitialize the BlockVector to contain as many blocks as there are
       * index sets given in the input argument, according to the parallel
       * distribution of the individual components described in the maps.
       *
       * If <tt>omit_zeroing_entries==false</tt>, the vector is filled with
       * zeros.
       */
      void
      reinit(const std::vector<IndexSet> &parallel_partitioning,
             const MPI_Comm               communicator         = MPI_COMM_WORLD,
             const bool                   omit_zeroing_entries = false);

      /**
       * Reinit functionality. This function destroys the old vector content
       * and generates a new one based on the input partitioning. In addition
       * to just specifying one index set as in all the other methods above,
       * this method allows to supply an additional set of ghost entries.
       * There are two different versions of a vector that can be created. If
       * the flag @p vector_writable is set to @p false, the vector only
       * allows read access to the joint set of @p parallel_partitioning and
       * @p ghost_entries. The effect of the reinit method is then equivalent
       * to calling the other reinit method with an index set containing both
       * the locally owned entries and the ghost entries.
       *
       * If the flag @p vector_writable is set to true, this creates an
       * alternative storage scheme for ghost elements that allows multiple
       * threads to write into the vector (for the other reinit methods, only
       * one thread is allowed to write into the ghost entries at a time).
       */
      void
      reinit(const std::vector<IndexSet> &partitioning,
             const std::vector<IndexSet> &ghost_values,
             const MPI_Comm               communicator    = MPI_COMM_WORLD,
             const bool                   vector_writable = false);

      /**
       * Initialize each block given to each parallel partitioning described in
       * @p partitioners.
       *
       * You can decide whether your vector will contain ghost elements with
       * @p make_ghosted.
       *
       * The parameter @p vector_writable only has effect on ghosted vectors
       * and is ignored for non-ghosted vectors.
       */
      void
      reinit(
        const std::vector<std::shared_ptr<const Utilities::MPI::Partitioner>>
          &        partitioners,
        const bool make_ghosted    = true,
        const bool vector_writable = false);

      /**
       * Change the dimension to that of the vector <tt>V</tt>. The same
       * applies as for the other reinit() function.
       *
       * The elements of <tt>V</tt> are not copied, i.e.  this function is the
       * same as calling <tt>reinit (V.size(), omit_zeroing_entries)</tt>.
       *
       * Note that you must call this (or the other reinit() functions)
       * function, rather than calling the reinit() functions of an individual
       * block, to allow the block vector to update its caches of vector
       * sizes. If you call reinit() on one of the blocks, then subsequent
       * actions on this object may yield unpredictable results since they may
       * be routed to the wrong block.
       */
      void
      reinit(const BlockVector &V, const bool omit_zeroing_entries = false);

      /**
       * Change the number of blocks to <tt>num_blocks</tt>. The individual
       * blocks will get initialized with zero size, so it is assumed that the
       * user resizes the individual blocks by herself in an appropriate way,
       * and calls <tt>collect_sizes</tt> afterwards.
       */
      void
      reinit(const size_type num_blocks);

      /**
       * This reinit function is meant to be used for parallel calculations
       * where some non-local data has to be used. The typical situation where
       * one needs this function is the call of the
       * FEValues<dim>::get_function_values function (or of some derivatives)
       * in parallel. Since it is usually faster to retrieve the data in
       * advance, this function can be called before the assembly forks out to
       * the different processors. What this function does is the following:
       * It takes the information in the columns of the given matrix and looks
       * which data couples between the different processors. That data is
       * then queried from the input vector. Note that you should not write to
       * the resulting vector any more, since the some data can be stored
       * several times on different processors, leading to unpredictable
       * results. In particular, such a vector cannot be used for matrix-
       * vector products as for example done during the solution of linear
       * systems.
       */
      void
      import_nonlocal_data_for_fe(const TrilinosWrappers::BlockSparseMatrix &m,
                                  const BlockVector &                        v);

      /**
       * Return if this Vector contains ghost elements.
       *
       * @see
       * @ref GlossGhostedVector "vectors with ghost elements"
       */
      bool
      has_ghost_elements() const;

      /**
       * Swap the contents of this vector and the other vector <tt>v</tt>. One
       * could do this operation with a temporary variable and copying over
       * the data elements, but this function is significantly more efficient
       * since it only swaps the pointers to the data of the two vectors and
       * therefore does not need to allocate temporary storage and move data
       * around.
       *
       * Limitation: right now this function only works if both vectors have
       * the same number of blocks. If needed, the numbers of blocks should be
       * exchanged, too.
       *
       * This function is analogous to the swap() function of all C++
       * standard containers. Also, there is a global function swap(u,v) that
       * simply calls <tt>u.swap(v)</tt>, again in analogy to standard
       * functions.
       */
      void
      swap(BlockVector &v);

      /**
       * Print to a stream.
       */
      void
      print(std::ostream &     out,
            const unsigned int precision  = 3,
            const bool         scientific = true,
            const bool         across     = true) const;

      /**
       * Exception
       */
      DeclException0(ExcIteratorRangeDoesNotMatchVectorSize);

      /**
       * Exception
       */
      DeclException0(ExcNonMatchingBlockVectors);
    };



    /*-------------------------- Inline functions ---------------------------*/
    inline BlockVector::BlockVector(
      const std::vector<IndexSet> &parallel_partitioning,
      const MPI_Comm               communicator)
    {
      reinit(parallel_partitioning, communicator, false);
    }



    inline BlockVector::BlockVector(
      const std::vector<IndexSet> &parallel_partitioning,
      const std::vector<IndexSet> &ghost_values,
      const MPI_Comm               communicator,
      const bool                   vector_writable)
    {
      reinit(parallel_partitioning,
             ghost_values,
             communicator,
             vector_writable);
    }



    inline BlockVector::BlockVector(const size_type num_blocks)
    {
      reinit(num_blocks);
    }



    inline BlockVector::BlockVector(const BlockVector &v)
      : dealii::BlockVectorBase<MPI::Vector>()
    {
      this->block_indices = v.block_indices;

      this->components.resize(this->n_blocks());
      for (unsigned int i = 0; i < this->n_blocks(); ++i)
        this->components[i] = v.components[i];

      this->collect_sizes();
    }



    inline BlockVector::BlockVector(BlockVector &&v) noexcept
    {
      // initialize a minimal, valid object and swap
      reinit(0);
      swap(v);
    }



    template <typename Number>
    BlockVector &
    BlockVector::operator=(const ::dealii::BlockVector<Number> &v)
    {
      // we only allow assignment to vectors with the same number of blocks
      // or to an empty BlockVector
      Assert(this->n_blocks() == 0 || this->n_blocks() == v.n_blocks(),
             ExcDimensionMismatch(this->n_blocks(), v.n_blocks()));

      if (this->n_blocks() != v.n_blocks())
        this->block_indices = v.get_block_indices();

      this->components.resize(this->n_blocks());
      for (unsigned int i = 0; i < this->n_blocks(); ++i)
        this->components[i] = v.block(i);

      this->collect_sizes();

      return *this;
    }



    inline bool
    BlockVector::has_ghost_elements() const
    {
      bool ghosted = block(0).has_ghost_elements();
#  ifdef DEBUG
      for (unsigned int i = 0; i < this->n_blocks(); ++i)
        Assert(block(i).has_ghost_elements() == ghosted, ExcInternalError());
#  endif
      return ghosted;
    }



    inline void
    BlockVector::swap(BlockVector &v)
    {
      std::swap(this->components, v.components);

      dealii::swap(this->block_indices, v.block_indices);
    }



    /**
     * Global function which overloads the default implementation of the C++
     * standard library which uses a temporary object. The function simply
     * exchanges the data of the two vectors.
     *
     * @relatesalso TrilinosWrappers::MPI::BlockVector
     */
    inline void
    swap(BlockVector &u, BlockVector &v)
    {
      u.swap(v);
    }

  } /* namespace MPI */

} /* namespace TrilinosWrappers */

/** @} */


namespace internal
{
  namespace LinearOperatorImplementation
  {
    template <typename>
    class ReinitHelper;

    /**
     * A helper class used internally in linear_operator.h. Specialization for
     * TrilinosWrappers::MPI::BlockVector.
     */
    template <>
    class ReinitHelper<TrilinosWrappers::MPI::BlockVector>
    {
    public:
      template <typename Matrix>
      static void
      reinit_range_vector(const Matrix &                      matrix,
                          TrilinosWrappers::MPI::BlockVector &v,
                          bool omit_zeroing_entries)
      {
        v.reinit(matrix.locally_owned_range_indices(),
                 matrix.get_mpi_communicator(),
                 omit_zeroing_entries);
      }

      template <typename Matrix>
      static void
      reinit_domain_vector(const Matrix &                      matrix,
                           TrilinosWrappers::MPI::BlockVector &v,
                           bool omit_zeroing_entries)
      {
        v.reinit(matrix.locally_owned_domain_indices(),
                 matrix.get_mpi_communicator(),
                 omit_zeroing_entries);
      }
    };

  } // namespace LinearOperatorImplementation
} /* namespace internal */


/**
 * Declare dealii::TrilinosWrappers::MPI::BlockVector as distributed vector.
 */
template <>
struct is_serial_vector<TrilinosWrappers::MPI::BlockVector> : std::false_type
{};

DEAL_II_NAMESPACE_CLOSE

#endif // DEAL_II_WITH_TRILINOS

#endif
